9 Metrics for SaaS Product Managers

9 Metrics for SaaS Product Managers

Every company wants to be data-driven these days and for good reason: thorough analysis and testing of hypotheses using data is the best and most sustainable way of improving products and services. However, the available techniques that product managers can use to make data-driven decisions differ greatly between product categories. Where creators of consumer-targeted mobile or web products can often rely on a glut of data and employ techniques like A/B testing and MVT on a regular basis, with enterprise SaaS products and a naturally much smaller base of data, statistical significance becomes an issue, requiring product managers to rely on data-informed decision making instead. Data-driven and informed decision making rests on one simple assumption: you know what you are optimizing for and what you are optimizing for is the right thing.

This leads us to the question of selecting the right metrics and KPIs to optimize for. Theoretically, there is only one metric that should matter for a company: profit.

In reality, profit is an elusive and often undesirable KPI, as it is not always reflective of company strategy (at least in the mid term, sacrificing growth for profit can be harmful and it is a trailing indicator of product success.) Once you know how a product decision affects profit, it can often be too late. What product managers for SaaS products need are metrics that are descriptive of a particular aspect of the customer or product life cycle, easy to measure, comparable and ideally leading indicators of higher value KPIs like profit.

Metrics are not only required to allow for data-driven decision-making in product management, but also as means of effective communication with product stakeholders. For this reason, a series of standard metrics for SaaS products have emerged:

TAM (Total Addressable Market) — before you start building a product, know what the size of the market is. TAM is the standard way of measuring market size and it is defined as the total sum of revenue all competitors in a particular market are generating in a given year. This definition makes it one of the hardest metrics to determine, because it would require knowing the actual revenue of all of your competitors, which is often hard when you can’t even estimate the total number of your competitors. Instead of buying expensive market research for a not yet clearly defined market, startup product managers should rely on a rough Fermi-estimation to get a feeling of the viability of a market. Market research firms like IDC or Gartner often offer very detailed reports on market size and growth, but this information comes at a considerable price and often covers only established markets, i.e. markets where investors and vendors already know that it exists and want to assess the viability of their investment.

ARR (Annual Recurring Revenue) — ARR and its little brother MRR (Monthly Recurring Revenue) are the most fundamental metrics to track, and the basis for the calculation of the following metrics. Based on your billing cycle, ARR is more appropriate if you are dealing in large enterprise accounts with multi-year contracts and yearly billing cycles, while MRR works better for SMB and consumer offerings that have a significant share of customers paying month to month. Which one you chose, is not as important as every seven year old will be able to tell you that the conversion factor between the two is exactly twelve.

Retention rate and churn rate — like many SaaS metrics, retention rate and churn rate come in pairs. Retention rate is simply the percentage of customers who renew their contract at the end of the term, while churn rate is the percentage of customers who don’t renew the contact and actively or passively cancel the subscription. Retention rate and churn rate should again be based on the typical term length and billing period, so if you are dealing in enterprise SaaS, retention rate is number of customers who extended their contract in the period / number of customers whose contracts where up for extension. Churn rate is 1 – retention rate.

NPS (Net Promoter Score) — Unlike the metrics mentioned so far, Net Promoter Score is not directly related to product revenue, but the metric has been found to be a good leading indicator of customer churn. Despite its many shortcomings it is established as a quasi industry standard, every customer support tool supports measuring it and it allows for easy benchmarking.

Net promoter score is measured by asking customer “How likely is it that you would recommend our product to a friend or colleague?” Customers submit their responses on a scale from 0 to 10. To calculate the score, subtract the numbers of detractors (people voting 0-6) from the number of promoters (voting 9 or 10) and divide by the total number of responses.

ACV (Annual Contract Value) and TCV (Total Contract Value) are the total committed value for a customer for a year and the total contract size. This is especially important when multi-year deals are offered, and no month to month or year-to-year cancellations are possible. Annual and total contract value can be calculated on an individual deal basis, but in order to estimate average ACV you can simply calculate ARR / number of customers.

Gross margin — in order to calculate the gross margin of your product, consider only the cost your product is causing to the company that is in direct relationship with providing the service, not selling or building it. In most cases, this includes cost for infrastructure, operations and support. Everything else is technically not required to keep the lights on and provide the same quality of service. Gross margin is (ARR – yearly operating cost) / ARR. If you end up with a negative value here, it’s time to stop reading this blog post and start thinking about switching to a more sustainable business model.

CLTV (Customer Life Time Value) is one of the most valuable, but also most difficult to calculate metrics in the toolkit, as it combines a lot of the metrics above. It describes the total gross profit you can expect per customer over its estimated life time and helps you estimate the effectiveness of your marketing and sales process and answer the question whether you are generating enough value for customers to operate a sustainable business. In order to calculate:

TCV multiply ARR with gross margin and divide by yearly churn rate.

One of the most powerful properties of the CLTV metric is that a reduction of churn rate is equally effective as an increase in sales price or a reduction in operating cost. In reality, reducing churn rate is often the most sustainable and predictable strategy available to companies.

CAC (Customer Acquisition Cost) — remember how we only considered operating cost, i.e. support, infrastructure and operations cost when calculating gross margin, leaving out cost of marketing and sales? CAC is what fixes this. It calculates the total cost of customer acquisition by simply combining all sales, pre-sales and marketing cost and dividing it by the number of customers won in the same period. While CLTV tells you what you can expect to get out of a customer, CAC tells you what you have to spend to close a new customer. As long as CAC is smaller than CLTV, you are looking at a sustainable business, but not necessarily a massively growing one. For this you need our last SaaS metric:

CAC Recovery Period – this is the theoretical time it takes to recover the initial cost of customer acquisition and turn a paying customer into a profitable. You want this period to be significantly shorter than you average contract length.

To determine CAC recovery period, calculate CAC / ARR * gross margin.

Again, a higher margin will help you run customers profitably faster.

With this basic framework of metrics you can comprehensible describe the revenue, growth, operating cost and marketing cost of your product. Depending on the depth of your analysis, you can further break down by customer group to determine niches where your product is particularly profitable, or establish additional usage metrics that help you identify customers most likely to churn or upsell.

How do you use these metrics for your products? Let us know, and tweet at us!

Lars Trieloff is Director of Product Management at Blue Yonder, where he helps companies to establish automated data-driven decision making, based on Blue Yonder’s predictive application platform. With metrics being his déformation professionnelle, Lars is also an avid user of quantified self tracking tools. You can follow Lars on Twitter or read more on his blog.

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